As I was writing this article, it was perhaps not so coincidental that I took a break and made a phone call to a home appliance customer support line for a microwave that we owned.I soon found myself trapped in an automated agentic AI phone system with no way out and no way to reach a human agent. I finally gave up, and called a local appliance company, where a human salesman gave me the answer that I needed.The experience is common. There are millions of consumers who experience frustration with automated phone systems and chat services that have no way of routing them to the person (or function) that can help them resolve their issues.Companies know this, but its not stopping them from adopting agentic AI at breakneck speeds, as evidenced by a projected market growth for agentic AI of 43.8% CAGR (compound annual growth rate) between now and 2034. Its all the more reason for CIOs to get involved early with agentic AI to make sure that it works for people as well as for systems.Just What Is Agentic AI and How Does it Work?In a 2024 interview with the Harvard Business Review, Enver Cetin, an AI expert at global experience engineering firm Ciklum, said, [Agentic AI] refers to AI systems and models that can act autonomously to achieve goals without the need for constant human guidance. The agentic AI system understands what the goal or vision of the user is and the context to the problem they are trying to solve.Related:Agentic AI uses a combination of machine learning (ML), natural language processing (NLP) and automation to do this. Its mission to make decisions and act on them.Companies can design agentic AI systems that require a final human authorization for some decisions, or they can make the agentic AI completely autonomous, so it makes decisions on its own.Most agentic AI adoptions are being sponsored and funded by end-user departments, which suggests that IT may or may not be in on the initial evaluations and buy decisions.Gartner cites an early example of how agentic AI can be deployed in retail.AI-enabled machine customers -- or nonhuman economic actors that obtain goods and services in exchange for payment --are examples of increasingly common intelligent agents. In the near future, they will make optimized decisions on behalf of human customers based on preset rules and will quickly evolve toward greater autonomy and inferring of needs.So, knowing that agentic AI is coming, and that IT might also be the last to know about an agentic AI buy decision, what should CIOs be doing?Related:Key CIO Points for Agentic AIWork up ITs agentic AI strategy now. Agentic AI has enormous potential. It can automate rote business operations and decision making, and IT needs to strategize for it.In a sense, agentic AI and what it can do has already been known in previous incarnations, such as automated loan decisioning software that has existed and functioned capably in bank lending departments for decades. However, now the needle is moving toward more autonomy. Business users will decide where they want to use agentic AI, but it will be ITs responsibility to ask the questions about system and process integration, governance and security that will enable agentic AI to be used safely and to best advantage.In this environment, an immediate CIO goal should be to participate with users in agentic AI strategy discussions so that best use business cases can be identified. Then, there should be a collaborative strategy with users and IT that takes into account not only business process streamlining and automation, but process exception handling, process and system integration. Plus, they should address user and IT training, security and governance. Although agentic AI will be driven by users, this is no time for IT to take a back seat.Related:Discuss security and failover. Your sales department might fund and adopt agentic AI to autonomously execute the mechanisms of product ordering, but what happens if a bad actor penetrates the agentic AI and locks it down for ransom or, what if that bad actor invades agentic AI software and injects malware or faulty algorithms that compromise and endanger the function?The sales team will quickly pivot to IT to fix these issues, so CIOs should be proactively querying sales and agentic AI vendors about the types of security that come with the agentic AI. There should be a company review of the AI to ensure that it complies with corporate security and governance standards. Questions should also be asked as to whether there is a failover to a human agent if the agentic AI fails or sputters. There should be a defined failover procedure in the company disaster recovery plan that provides for human ability to override or take over from agentic AI if that becomes necessary.Be prepared for project inclusion, whether you want it or not! IT may not be involved in initial agentic AI purchase decisions, but it will surely be pulled into agentic AI projects, because the AI wont get very far if it isnt integrated with other corporate systems.Accordingly, IT should ensure that user-IT agentic AI project discussions focus on system integration, and on the clear definition of a project test bed for agentic AI integration into business processes themselves.A successful business process integration addresses user training and readiness for a new technology, and what will happen if the agentic AI fails or begins to make poor decisions.CIOs shouldnt shy away from insisting that these process-oriented elements are tasked in agentic AI projects, because if anything goes wrong after the technology is placed into production, it will likely be blamed on the system.